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Bayesian Optimization Jobs in Princeton Junction, NJ

Improve existing strategies and portfolio optimization * Execution monitoring * Be a core ... Bayesian inference-as well as techniques for dealing with errors that can occur, such as auto ...

AI Researcher

New York, NY · On-site

$175K - $250K/yr

... optimization, signal processing, filtering and smoothing, time-series analysis, hidden Markov models, high-dimensional data analysis, vector quantization, decision tree methods, EM methods, Bayesian ...

... optimization, signal processing, filtering and smoothing, time-series analysis, hidden Markov models, high-dimensional data analysis, vector quantization, decision tree methods, EM methods, Bayesian ...

Senior AI/ML Engineer

New York, NY · On-site

$95K - $125K/yr

Use statistical inference (Bayesian and Markov Chain Monte Carlo methods) for probabilistic design ... Use constrained multi-objective optimization, and other computational methods for design space ...

New

Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data ...

Showing results 21-40

Bayesian Optimization information

What is the difference between Bayesian Optimization vs Data Scientist?

AspectBayesian OptimizationData Scientist
Primary FocusOptimizing complex functions and hyperparametersAnalyzing data, building models, deriving insights
Required SkillsStatistics, probability, machine learning, programmingStatistics, programming, data analysis, visualization
Work EnvironmentResearch labs, AI/ML teams, R&D departmentsBusiness, tech companies, consulting firms
Common ToolsPython, R, Bayesian libraries (e.g., GPy, scikit-optimize)Python, R, SQL, visualization tools

Bayesian Optimization is a specialized technique used within machine learning and AI to efficiently tune hyperparameters or optimize functions. Data Scientists often utilize Bayesian Optimization as part of their toolkit but have broader responsibilities, including data analysis, modeling, and reporting. While Bayesian Optimization focuses on optimization tasks, Data Scientists work on understanding and interpreting data to inform business decisions.

What job categories do people searching Bayesian Optimization jobs in Princeton Junction, NJ look for? The top searched job categories for Bayesian Optimization jobs in Princeton Junction, NJ are:
What cities near Princeton Junction, NJ are hiring for Bayesian Optimization jobs? Cities near Princeton Junction, NJ with the most Bayesian Optimization job openings:
Infographic showing various Bayesian Optimization job openings in Princeton Junction, NJ as of August 2026, with employment types broken down into 1% Internship, 84% Full Time, 10% Part Time, and 5% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.

Quantitative Researcher - Macro

Point72

New York, NY • On-site

$150K - $200K/yr

Full-time

Re-posted yesterday


Job description

About Cubist

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

Role

Quantitative researcher to help build out a systematic macro (futures, FX, and vol) strategies. Core focus will be working on mid-frequency alpha strategies.

Job Description
  • Develop systematic trading models across FX, commodities, fixed income, and equity markets
  • Alpha idea generation, backtesting, and implementation
  • Assist in building, maintenance, and continual improvement of production and trading environments
  • Evaluate new datasets for alpha potential
  • Improve existing strategies and portfolio optimization
  • Execution monitoring
  • Be a core contributor to growing the investment process and research infrastructure of the team
Desirable Candidates
  • Masters or PhD in mathematics, statistics, physics or other quantitative discipline. PhD in statistics or machine learning is a plus
  • Experience in quantitative trading, ideally in FX or futures
  • Experience with alpha research, portfolio construction and optimization
  • Experience building statistical/technical, fundamental, and data driven signals
  • Experience synthesizing predictive signals for both cross-sectional and time-series models
  • Strong experience with data exploration, dimension reduction, and feature engineering
  • Thorough understanding of and comfort using a variety of regression techniques-including OLS, MLS, Ridge, Lasso, and Bayesian inference-as well as techniques for dealing with errors that can occur, such as auto-correlation and heteroskedasticity
  • Experience managing and running risk is a strong plus
  • Proficiency in Python using the machine learning stack-numpy, pandas, scikit-learn, etc.
  • Creative mindset
  • Strong time management ability-the ability to manage multiple tasks and deadlines in a fast-paced environment
  • High degree of drive and energy-must be a self-starter
  • Ability to work cooperatively with all levels of staff and to thrive in a team-oriented environment
  • Commitment to the highest ethical standards and who act with professionalism and integrity at all times


The annual base salary range for this role is $150,000-$200,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.